ML Framework Engineer, Graphics, Game and ML

Apple Inc

Confirmed live yesterday Trusted

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$150,400–$277,600 / yr
Posted
148 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $225k
This role $214k
$135k most similar roles pay here $293k

This role pays less than 52% of similar roles. Most pay $195,787–$254,750 — the shaded band above. At the midpoint, this role pays about $214k versus about $225k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · ML Framework Engineer, Graphics, Game and ML

ML Framework (MetalLM) Engineer, Graphics, Game and ML joins the Server ML Frameworks team within GPU, Graphics and Machine Learning to enable Apple Intelligence through high-performance distributed inference of GenAI applications like LLMs. You will develop kernel and compiler level optimizations while implementing distributed compute strategies including data, tensor, pipeline, and expert parallelism. The role involves applying advanced model optimization techniques such as speculation, quantization, and compression to maximize throughput and minimize latency on custom-built server hardware. You will collaborate with hardware and systems teams to align software performance with capabilities. Required skills include C/C++/ObjC programming, GPU kernel development using Metal or CUDA, and experience with distributed training or inference. Preferred qualifications include knowledge of graph compilers like Triton or LLVM and understanding of LLM and Diffusion based model architectures.

What you'll do

  • Optimize code for scalable ML inference using distributed strategies like data, tensor, pipeline, and expert parallelism.
  • Develop kernel and compiler level optimizations to maximize performance across various server hardware families.
  • Apply model optimization techniques including speculation, quantization, and compression to improve throughput and reduce latency.
  • Analyze and improve key performance metrics such as end-to-end latency, TTFT, TBOT, and memory footprint.
  • Align software performance with hardware capabilities through close collaboration with hardware and compiler teams.
  • Build production-grade solutions for high-throughput GPU execution on Apple Silicon.

What we're looking for

  • At least 3 years of programming and problem-solving experience with C, C++, or Objective-C.
  • Experience in GPU kernel development and optimizations using compute programming models like Metal or CUDA.
  • Experience with distributed training or inference techniques.
  • Experience with system-level programming and computer architecture.
  • Experience with graph compilers such as CuTE, CuTile, Triton, OpenXLA, or LLVM.
  • Strong understanding of LLM and Diffusion-based model architectures.

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